Submission¶

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [1]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px

init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [2]:
#load data
df = px.data.gapminder()
df.head()
Out[2]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:¶

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [13]:
# Filter the DataFrame to select data for the year 2007
df_2007 = df[df['year'] == 2007]

# Group the filtered data by continent and calculate the sum of numeric columns
df_2007_new = df_2007.groupby('continent').sum().reset_index()

# Create a bar chart using Plotly Express
fig = px.bar(df_2007_new, x='pop', y='continent', color='continent')

# Update the layout for the x-axis to order continents in alphabetical order
fig.update_xaxes(categoryorder="category ascending")

# Display the resulting chart
fig.show()
00.5B1B1.5B2B2.5B3B3.5B4BOceaniaEuropeAsiaAmericasAfrica
continentAfricaAmericasAsiaEuropeOceaniapopcontinent
plotly-logomark
In [5]:
# YOUR CODE HERE
05B10B15B20B25B30BOceaniaEuropeAsiaAmericasAfrica
popcontinent
plotly-logomark

Question 2:¶

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [16]:
# Filter the DataFrame to select data for the year 2007
df_2007 = df[df['year'] == 2007]

# Group the filtered data by continent and calculate the sum of numeric columns
df_2007_new = df_2007.groupby('continent').sum().reset_index()

# Create a bar chart using Plotly Express
fig = px.bar(df_2007_new, x='pop', y='continent', color='continent')

# Update the layout for the y-axis to order continents in total population
fig.update_yaxes(categoryorder="total ascending")

# Display the resulting chart
fig.show()
00.5B1B1.5B2B2.5B3B3.5B4BOceaniaEuropeAmericasAfricaAsia
continentAfricaAmericasAsiaEuropeOceaniapopcontinent
plotly-logomark
In [6]:
# YOUR CODE HERE
05B10B15B20B25B30BOceaniaEuropeAfricaAmericasAsia
popcontinent
plotly-logomark

Question 3:¶

Add text to each bar that represents the population

In [18]:
# Filter the DataFrame to select data for the year 2007
df_2007 = df[df['year'] == 2007]

# Group the filtered data by continent and calculate the sum of numeric columns
df_2007_new = df_2007.groupby('continent').sum().reset_index()

# Create a bar chart using Plotly Express
fig = px.bar(df_2007_new, x='pop', text = 'pop', y='continent', color='continent')

# Update the layout for the y-axis to order continents in total population
fig.update_yaxes(categoryorder="total ascending")

# Customize the text labels on the bars: format with two decimal places and position them outside the bars
fig.update_traces(texttemplate='%{text:.2s}', textposition='outside')

# Display the resulting chart
fig.show()
930M900M3.8G590M25M00.5B1B1.5B2B2.5B3B3.5B4BOceaniaEuropeAmericasAfricaAsia
continentAfricaAmericasAsiaEuropeOceaniapopcontinent
plotly-logomark
In [7]:
# YOUR CODE HERE
6.2G7.4G31G6.2G210M05B10B15B20B25B30BOceaniaEuropeAfricaAmericasAsia
popcontinent
plotly-logomark

Question 4:¶

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [60]:
df = px.data.gapminder()
fig = px.histogram(df, x='pop', y='continent', color='continent', animation_frame="year", animation_group="country", width = 1000, height = 400, range_x=[0, 4E9])
fig.update_layout(showlegend=False)
fig.update_yaxes(categoryorder="total ascending")
fig.show()
00.5B1B1.5B2B2.5B3B3.5B4BOceaniaAfricaAmericasEuropeAsia
year=1952195219571962196719721977198219871992199720022007sum of popcontinentâ–¶â—¼
plotly-logomark
In [9]:
# YOUR CODE HERE
00.5B1B1.5B2B2.5B3B3.5B4BOceaniaAfricaAmericasEuropeAsia
year=1952195219571962196719721977198219871992199720022007popcontinentâ–¶â—¼
plotly-logomark

Question 5:¶

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [68]:
df = px.data.gapminder()
fig = px.bar(df, x='pop', y='country', color='country', animation_frame="year", animation_group="country")
fig.update_layout(showlegend=False)
fig.update_yaxes(categoryorder="total ascending")

fig.update_layout(autosize=False,
    width=1000,
    height=500,)

fig.show()
0100M200M300M400M500MSao Tome and PrincipeReunionOmanCongo, Rep.SingaporeLebanonEl SalvadorSomaliaBoliviaNorwayCroatiaMadagascarUgandaAustriaAfghanistanCzech RepublicCongo, Dem. Rep.EthiopiaVietnamItalyIndia
year=1952195219571962196719721977198219871992199720022007popcountryâ–¶â—¼
plotly-logomark
In [11]:
# YOUR CODE HERE
00.2B0.4B0.6B0.8B1B1.2B1.4BSao Tome and PrincipeReunionOmanCongo, Rep.SingaporeLebanonEl SalvadorSomaliaBoliviaNorwayCroatiaMadagascarUgandaAustriaAfghanistanCzech RepublicCongo, Dem. Rep.EthiopiaVietnamItalyIndia
year=1952195219571962196719721977198219871992199720022007popcountryâ–¶â—¼
plotly-logomark

Question 6:¶

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [69]:
df = px.data.gapminder()
fig = px.bar(df, x='pop', y='country', color='country', animation_frame="year", animation_group="country")
fig.update_layout(showlegend=False)
fig.update_yaxes(categoryorder="total ascending")

fig.update_layout(autosize=False,
    width=1000,
    height=1000,)

fig.show()
0100M200M300M400M500MSao Tome and PrincipeIcelandEquatorial GuineaSwazilandBotswanaMauritiusTrinidad and TobagoCongo, Rep.PanamaWest Bank and GazaTogoJamaicaSloveniaIsraelEl SalvadorPuerto RicoDominican RepublicGuineaSenegalMalawiZimbabweNorwaySlovak RepublicMaliFinlandBurkina FasoSwitzerlandVenezuelaUgandaMozambiqueSerbiaBulgariaPeruSudanAustraliaCzech RepublicHungaryColombiaCanadaArgentinaKorea, Rep.TurkeyVietnamNigeriaBangladeshBrazilJapanChina
year=1952195219571962196719721977198219871992199720022007popcountryâ–¶â—¼
plotly-logomark
In [12]:
# YOUR CODE HERE
00.2B0.4B0.6B0.8B1B1.2B1.4BSao Tome and PrincipeIcelandEquatorial GuineaSwazilandBotswanaMauritiusTrinidad and TobagoCongo, Rep.PanamaWest Bank and GazaTogoJamaicaSloveniaIsraelEl SalvadorPuerto RicoDominican RepublicGuineaSenegalMalawiZimbabweNorwaySlovak RepublicMaliFinlandBurkina FasoSwitzerlandVenezuelaUgandaMozambiqueSerbiaBulgariaPeruSudanAustraliaCzech RepublicHungaryColombiaCanadaArgentinaKorea, Rep.TurkeyVietnamNigeriaBangladeshBrazilJapanChina
year=1952195219571962196719721977198219871992199720022007popcountryâ–¶â—¼
plotly-logomark

Question 7:¶

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [73]:
df = px.data.gapminder()
fig = px.bar(df, x='pop', y='country', color='country', animation_frame="year", animation_group="country")
fig.update_layout(showlegend=False)
fig.update_yaxes(categoryorder="total ascending")
fig.update_yaxes(range=(131.5,141.5))

fig.update_layout(autosize=False,
    width=1000,
    height=500,)

fig.show()
0100M200M300M400M500MBangladeshItalyUnited KingdomBrazilGermanyIndonesiaJapanUnited StatesIndiaChina
year=1952195219571962196719721977198219871992199720022007popcountryâ–¶â—¼
plotly-logomark
In [13]:
# YOUR CODE HERE
00.2B0.4B0.6B0.8B1B1.2B1.4BBangladeshItalyUnited KingdomBrazilGermanyIndonesiaJapanUnited StatesIndiaChina
year=1952195219571962196719721977198219871992199720022007popcountryâ–¶â—¼
plotly-logomark